def getScalesWithCut(dir,
fileNames,
cut='OSTight',
massWindow=True,
type='DY'):
yieldsHist = {}
xs = {}
scales = {}
iFiles = []
iTrees = []
for cat in fileNames.keys():
iFiles.append(r.TFile("%s/%s" % (dir, fileNames[cat])))
iTrees.append(iFiles[len(iFiles) - 1].Get('eventTree'))
yieldsHist[cat] = r.TH1F(cat, "", 6, 4, 10)
nEntries = iTrees[len(iTrees) - 1].GetEntries()
iTrees[len(iTrees) - 1].GetEntry(0)
xs[cat] = iTrees[len(iTrees) - 1].xs
for i in range(nEntries):
iTrees[len(iTrees) - 1].GetEntry(i)
signSelection, isoSelection, bTagSelection = makeWholeTools2.findCategory(
tree=iTrees[len(iTrees) - 1],
iso=1.0,
option='iso',
isData=False,
relaxedRegionOption=makeWholeSample_cfg.Relax,
isEmbed=False,
usePassJetTrigger=makeWholeSample_cfg.usePassJetTrigger,
nBtag='')
if signSelection == None or isoSelection == None:
continue
if iTrees[len(iTrees) - 1].HLT_Any == 0:
continue
if type == 'DY' and iTrees[len(iTrees) - 1].ZTT == 0:
continue
if type == 'ZLL' and iTrees[len(iTrees) - 1].ZLL == 0:
continue
if massWindow and not makeWholeTools2.passCut(
iTrees[len(iTrees) - 1], 'iso'):
continue
if cut != signSelection + isoSelection:
continue
yieldsHist[cat].Fill(
iTrees[len(iTrees) - 1].LHEProduct,
iTrees[len(iTrees) - 1].xs /
(iTrees[len(iTrees) - 1].initEvents + 0.0))
for i in range(2, 6, 1):
scales['%ijet' %
(i - 1)] = (yieldsHist['inclusive'].GetBinContent(i + 1) + 0.0
) / (yieldsHist['%ijet' %
(i - 1)].GetBinContent(i + 1) + 0.0)
return scales, xs
def getScalesWithCut(dir, fileNames, cut='OSTight', massWindow=True, type = 'DY'):
yieldsHist = {}
xs = {}
scales = {}
iFiles = []
iTrees = []
for cat in fileNames.keys():
iFiles.append(r.TFile("%s/%s" %(dir, fileNames[cat])))
iTrees.append(iFiles[len(iFiles)-1].Get('eventTree'))
yieldsHist[cat] = r.TH1F(cat, "", 6, 4, 10)
nEntries = iTrees[len(iTrees)-1].GetEntries()
iTrees[len(iTrees)-1].GetEntry(0)
xs[cat] = iTrees[len(iTrees)-1].xs
for i in range(nEntries):
iTrees[len(iTrees)-1].GetEntry(i)
signSelection, isoSelection, bTagSelection = makeWholeTools2.findCategory(tree = iTrees[len(iTrees)-1],
iso = 1.0,
option = 'iso',
isData = False,
relaxedRegionOption = makeWholeSample_cfg.Relax,
isEmbed = False,
usePassJetTrigger = makeWholeSample_cfg.usePassJetTrigger,
nBtag = '')
if signSelection == None or isoSelection == None:
continue
if iTrees[len(iTrees)-1].HLT_Any == 0:
continue
if type == 'DY' and iTrees[len(iTrees)-1].ZTT == 0:
continue
if type == 'ZLL' and iTrees[len(iTrees)-1].ZLL == 0:
continue
if massWindow and not makeWholeTools2.passCut(iTrees[len(iTrees)-1], 'iso'):
continue
if cut != signSelection+isoSelection:
continue
yieldsHist[cat].Fill(iTrees[len(iTrees)-1].LHEProduct, iTrees[len(iTrees)-1].xs/(iTrees[len(iTrees)-1].initEvents+0.0))
for i in range(2,6,1):
scales['%ijet' %(i-1)] = (yieldsHist['inclusive'].GetBinContent(i+1)+0.0)/(yieldsHist['%ijet' %(i-1)].GetBinContent(i+1)+0.0)
return scales, xs
def makeSyncNtuples(iLocation, cut, cutBTag, treepath, usePassJetTrigger, pairOption):
if '.root' in iLocation:
iFile = r.TFile(iLocation)
iTree = iFile.Get(treepath)
nEntries = iTree.GetEntries()
oFileName = iLocation[iLocation.rfind("/")+1:iLocation.rfind(".root")]
oFileName += '_sync'
oFileName += '%s_%s' %(cut, cutBTag)
if usePassJetTrigger:
oFileName += '_jetCut'
else:
iTree = r.TChain(treepath)
nEntries = tool.addFiles(ch=iTree, dirName=iLocation, knownEventNumber=0, maxFileNumber=-1, printTotalEvents = True)
oFileName = iLocation[iLocation.rfind("/")+1:iLocation.find("-SUB-TT")]
iTree.SetBranchStatus("*",1)
print iLocation
oFile = r.TFile("/nfs_scratch/zmao/samples/sync/%s.root" %oFileName,"recreate")
oTree = r.TTree('TauCheck', 'TauCheck')
run = array('i', [0])
lumi = array('i', [0])
evt = array('I', [0])
nTauPairs = array('i', [0])
npv = array('i', [0])
npu = array('i', [0])
rho = array('f', [0.])
mvis = array('f', [0.])
m_sv = array('f', [0.])
pt_sv = array('f', [0.])
eta_sv = array('f', [0.])
phi_sv = array('f', [0.])
pt_1 = array('f', [0.])
phi_1 = array('f', [0.])
eta_1 = array('f', [0.])
m_1 = array('f', [0.])
q_1 = array('i', [0])
iso_1 = array('f', [0.])
mva_1 = array('f', [0.])
byCombinedIsolationDeltaBetaCorrRaw3Hits_1 = array('f', [0.])
d0_1 = array('f', [0.])
dZ_1 = array('f', [0.])
mt_1 = array('f', [0.])
pt_2 = array('f', [0.])
phi_2 = array('f', [0.])
eta_2 = array('f', [0.])
m_2 = array('f', [0.])
q_2 = array('i', [0])
iso_2 = array('f', [0.])
mva_2 = array('f', [0.])
byCombinedIsolationDeltaBetaCorrRaw3Hits_2 = array('f', [0.])
d0_2 = array('f', [0.])
dZ_2 = array('f', [0.])
mt_2 = array('f', [0.])
againstElectronMVA3raw_1 = array('f', [0.])
againstElectronMVA3raw_2 = array('f', [0.])
againstMuonLoose2_1 = array('f', [0.])
againstMuonLoose2_2 = array('f', [0.])
againstMuonMedium2_1 = array('f', [0.])
againstMuonMedium2_2 = array('f', [0.])
againstMuonTight2_1 = array('f', [0.])
againstMuonTight2_2 = array('f', [0.])
met = array('f', [0.])
puweight = array('f', [0.])
mvamet = array('f', [0.])
mvametphi = array('f', [0.])
mvacov00 = array('f', [0.])
mvacov01 = array('f', [0.])
mvacov10 = array('f', [0.])
mvacov11 = array('f', [0.])
pzetavis = array('f', [0.])
pzetamiss = array('f', [0.])
pt_tt = array('f', [0.])
njets = array('i', [0])
njetspt20 = array('i', [0])
jpt_1 = array('f', [0.])
jeta_1 = array('f', [0.])
jphi_1 = array('f', [0.])
jptraw_1 = array('f', [0.])
jptunc_1 = array('f', [0.])
jmva_1 = array('f', [0.])
jlrm_1 = array('f', [0.])
jctm_1 = array('f', [0.])
jpass_1 = array('b', [0])
jpt_2 = array('f', [0.])
jeta_2 = array('f', [0.])
jphi_2 = array('f', [0.])
jptraw_2 = array('f', [0.])
jptunc_2 = array('f', [0.])
jmva_2 = array('f', [0.])
jlrm_2 = array('f', [0.])
jctm_2 = array('f', [0.])
jpass_2 = array('b', [0])
bpt_1 = array('f', [0.])
beta_1 = array('f', [0.])
bphi_1 = array('f', [0.])
bcsv_1 = array('f', [0.])
bpt_2 = array('f', [0.])
beta_2 = array('f', [0.])
bphi_2 = array('f', [0.])
bcsv_2 = array('f', [0.])
bpt_3 = array('f', [0.])
beta_3 = array('f', [0.])
bphi_3 = array('f', [0.])
bcsv_3 = array('f', [0.])
decayModeWeight_1 = array('f', [0.])
decayModeWeight_2 = array('f', [0.])
embeddedWeight = array('f', [0.])
m_bb = array('f', [0.])
m_ttbb = array('f', [0.])
nbtag = array('i', [0])
trigweight_1 = array('f', [0.])
trigweight_2 = array('f', [0.])
effweight = array('f', [0.])
DYWeight = array('f', [0.])
weight = array('f', [0.])
oTree.Branch("run", run, "run/I")
oTree.Branch("lumi", lumi, "lumi/I")
oTree.Branch("evt", evt, "evt/i")
oTree.Branch("nTauPairs", nTauPairs, "nTauPairs/I")
oTree.Branch("npv", npv, "npv/I")
oTree.Branch("npu", npu, "npu/I")
oTree.Branch("rho", rho, "rho/F")
oTree.Branch("mvis", mvis, "mvis/F")
oTree.Branch("m_sv", m_sv, "m_sv/F")
oTree.Branch("pt_sv", pt_sv, "pt_sv/F")
oTree.Branch("eta_sv", eta_sv, "eta_sv/F")
oTree.Branch("phi_sv", phi_sv, "phi_sv/F")
oTree.Branch("pt_1", pt_1, "pt_1/F")
oTree.Branch("phi_1", phi_1, "phi_1/F")
oTree.Branch("eta_1", eta_1, "eta_1/F")
oTree.Branch("m_1", m_1, "m_1/F")
oTree.Branch("q_1", q_1, "q_1/I")
oTree.Branch("iso_1", iso_1, "iso_1/F")
oTree.Branch("mva_1", mva_1, "mva_1/F")
oTree.Branch("byCombinedIsolationDeltaBetaCorrRaw3Hits_1", byCombinedIsolationDeltaBetaCorrRaw3Hits_1, "byCombinedIsolationDeltaBetaCorrRaw3Hits_1/F")
oTree.Branch("d0_1", d0_1, "d0_1/F")
oTree.Branch("dZ_1", dZ_1, "dZ_1/F")
oTree.Branch("mt_1", mt_1, "mt_1/F")
oTree.Branch("pt_2", pt_2, "pt_2/F")
oTree.Branch("phi_2", phi_2, "phi_2/F")
oTree.Branch("eta_2", eta_2, "eta_2/F")
oTree.Branch("m_2", m_2, "m_2/F")
oTree.Branch("q_2", q_2, "q_2/I")
oTree.Branch("iso_2", iso_2, "iso_2/F")
oTree.Branch("mva_2", mva_2, "mva_2/F")
oTree.Branch("byCombinedIsolationDeltaBetaCorrRaw3Hits_2", byCombinedIsolationDeltaBetaCorrRaw3Hits_2, "byCombinedIsolationDeltaBetaCorrRaw3Hits_2/F")
oTree.Branch("d0_2", d0_2, "d0_2/F")
oTree.Branch("dZ_2", dZ_2, "dZ_2/F")
oTree.Branch("mt_2", mt_2, "mt_2/F")
oTree.Branch("againstElectronMVA3raw_1", againstElectronMVA3raw_1, "againstElectronMVA3raw_1/F")
oTree.Branch("againstElectronMVA3raw_2", againstElectronMVA3raw_2, "againstElectronMVA3raw_2/F")
oTree.Branch("againstMuonLoose2_1", againstMuonLoose2_1, "againstMuonLoose2_1/F")
oTree.Branch("againstMuonLoose2_2", againstMuonLoose2_2, "againstMuonLoose2_2/F")
oTree.Branch("againstMuonMedium2_1", againstMuonMedium2_1, "againstMuonMedium2_1/F")
oTree.Branch("againstMuonMedium2_2", againstMuonMedium2_2, "againstMuonMedium2_2/F")
oTree.Branch("againstMuonTight2_1", againstMuonTight2_1, "againstMuonTight2_1/F")
oTree.Branch("againstMuonTight2_2", againstMuonTight2_2, "againstMuonTight2_2/F")
oTree.Branch("met", met, "met/F")
oTree.Branch("mvamet", mvamet, "mvamet/F")
oTree.Branch("mvametphi", mvametphi, "mvametphi/F")
oTree.Branch("mvacov00", mvacov00, "mvacov00/F")
oTree.Branch("mvacov01", mvacov01, "mvacov01/F")
oTree.Branch("mvacov10", mvacov10, "mvacov10/F")
oTree.Branch("mvacov11", mvacov11, "mvacov11/F")
oTree.Branch("pzetavis", pzetavis, "pzetavis/F")
oTree.Branch("pzetamiss", pzetamiss, "pzetamiss/F")
oTree.Branch("pt_tt", pt_tt, "pt_tt/F")
oTree.Branch("njets", njets, "njets/I")
oTree.Branch("njetspt20", njetspt20, "njetspt20/I")
oTree.Branch("nbtag", nbtag, "nbtag/I")
oTree.Branch("jpt_1", jpt_1, "jpt_1/F")
oTree.Branch("jeta_1", jeta_1, "jeta_1/F")
oTree.Branch("jphi_1", jphi_1, "jphi_1/F")
oTree.Branch("jptraw_1", jptraw_1, "jptraw_1/F")
oTree.Branch("jptunc_1", jptunc_1, "jptunc_1/F")
oTree.Branch("jmva_1", jmva_1, "jmva_1/F")
oTree.Branch("jctm_1", jctm_1, "jctm_1/F")
oTree.Branch("jpass_1", jpass_1, "jpass_1/B")
oTree.Branch("jpt_2", jpt_2, "jpt_2/F")
oTree.Branch("jeta_2", jeta_2, "jeta_2/F")
oTree.Branch("jphi_2", jphi_2, "jphi_2/F")
oTree.Branch("jptraw_2", jptraw_2, "jptraw_2/F")
oTree.Branch("jptunc_2", jptunc_2, "jptunc_2/F")
oTree.Branch("jmva_2", jmva_2, "jmva_2/F")
oTree.Branch("jctm_2", jctm_2, "jctm_2/F")
oTree.Branch("jpass_2", jpass_2, "jpass_2/B")
oTree.Branch("puweight", puweight, "puweight/F")
oTree.Branch("bpt_1", bpt_1, "bpt_1/F")
oTree.Branch("beta_1", beta_1, "beta_1/F")
oTree.Branch("bphi_1", bphi_1, "bphi_1/F")
oTree.Branch("bcsv_1", bcsv_1, "bcsv_1/F")
oTree.Branch("bpt_2", bpt_2, "bpt_2/F")
oTree.Branch("beta_2", beta_2, "beta_2/F")
oTree.Branch("bphi_2", bphi_2, "bphi_2/F")
oTree.Branch("bcsv_2", bcsv_2, "bcsv_2/F")
oTree.Branch("bpt_3", bpt_3, "bpt_3/F")
oTree.Branch("beta_3", beta_3, "beta_3/F")
oTree.Branch("bphi_3", bphi_3, "bphi_3/F")
oTree.Branch("bcsv_3", bcsv_3, "bcsv_3/F")
oTree.Branch("weight", weight, "weight/F")
oTree.Branch("embeddedWeight", embeddedWeight, "embeddedWeight/F")
oTree.Branch("DYWeight", DYWeight, "DYWeight/F")
oTree.Branch("m_bb", m_bb, "m_bb/F")
oTree.Branch("m_ttbb", m_ttbb, "m_ttbb/F")
oTree.Branch("trigweight_1", trigweight_1, "trigweight_1/F")
oTree.Branch("trigweight_2", trigweight_2, "trigweight_2/F")
oTree.Branch("effweight", effweight, "effweight/F")
oTree.Branch("decayModeWeight_1", decayModeWeight_1, "decayModeWeight_1/F")
oTree.Branch("decayModeWeight_2", decayModeWeight_2, "decayModeWeight_2/F")
counter = 0
lvClass = r.Math.LorentzVector(r.Math.PtEtaPhiM4D('double'))
b1 = lvClass()
b2 = lvClass()
tau1 = lvClass()
tau2 = lvClass()
eventMask = [(1, 6647, 2656734),(1, 14273, 2853418),(1, 9775, 3906872),(1, 38627, 7722260)]
for iEntry in range(nEntries):
track = False
iTree.GetEntry(iEntry)
tool.printProcessStatus(iEntry, nEntries, 'Saving to file %s.root' % (oFileName))
iBestPair = makeWholeTools2.findRightPair(iTree, pairOption)
if (iTree.RUN,iTree.LUMI, iTree.EVENT,) in eventMask:
print ''
print 'Event: %i Lumi: %i run: %i' %(iTree.EVENT, iTree.LUMI, iTree.RUN)
print 'pt1: %.2f pt2: %.2f CSVJ1: %.2f CSVJ2: %.2f b1Pt: %.2f b1Eta: %.2f b2Pt: %.2f b2Eta: %.2f' %(iTree.pt1.at(iBestPair), iTree.pt2.at(iBestPair), iTree.CSVJ1, iTree.CSVJ2, iTree.CSVJ1Pt, iTree.CSVJ1Eta, iTree.CSVJ2Pt, iTree.CSVJ2Eta)
print 'iso1: %.2f iso2: %.2f charge: %.2f' %(iTree.iso1.at(iBestPair), iTree.iso2.at(iBestPair), iTree.charge1.at(iBestPair) + iTree.charge2.at(iBestPair))
print 'svMass: %.2f mJJ: %.2f' %(iTree.svMass.at(iBestPair), iTree.mJJ)
print 'mvaMet: %.2f' %(iTree.met.at(iBestPair))
print 'met: %.2f' %(iTree.metUnc)
print 'fMass: %.2f' %(iTree.fMassKinFit)
print 'sampleName: %s' %iTree.sampleName
track = True
if iTree.HLT_Any == 0:
continue
if not makeWholeTools2.passCut(iTree, pairOption):
continue
if (iTree.nElectrons > 0 or iTree.nMuons > 0):
continue
signSelection, isoSelection, bTagSelection = makeWholeTools2.findCategory(tree = iTree,
iso = 1.0,
option = pairOption,
isData = True,
relaxedRegionOption = 'one1To4',
isEmbed = True,
usePassJetTrigger = usePassJetTrigger)
if signSelection == None or isoSelection == None or bTagSelection == None:
continue
tmpSelect = signSelection+isoSelection
if tmpSelect != cut:
continue
if not (cutBTag in bTagSelection) and (cutBTag != 'inclusive'):
continue
if iTree.ZTT == 0:
continue
trigweight_1[0] = iTree.triggerEff1
trigweight_2[0] = iTree.triggerEff2
effweight[0] = trigweight_1[0] * trigweight_2[0]
nTauPairs[0] = len(iTree.pt1)
run[0] = iTree.RUN
evt[0] = iTree.EVENT
npv[0] = iTree.vertices
npu[0] = int(iTree.puTruth)
lumi[0] = iTree.LUMI
rho[0] = iTree.Rho
mvis[0] = (tau1+tau2).mass()
m_sv[0] = iTree.svMass.at(iBestPair)
pt_sv[0] = iTree.svPt.at(iBestPair)
eta_sv[0] = iTree.svEta.at(iBestPair)
phi_sv[0] = iTree.svPhi.at(iBestPair)
pt_1[0] = iTree.pt1.at(iBestPair)
eta_1[0] = iTree.eta1.at(iBestPair)
phi_1[0] = iTree.phi1.at(iBestPair)
m_1[0] = iTree.m1.at(iBestPair)
q_1[0] = int(iTree.charge1.at(iBestPair))
iso_1[0] = iTree.tau1MVAIso
mva_1[0] = 0
byCombinedIsolationDeltaBetaCorrRaw3Hits_1[0] = iTree.iso1.at(iBestPair)
d0_1[0] = iTree.d0_1
dZ_1[0] = iTree.l1dz
# mt_1[0] = iTree.mt1
pt_2[0] = iTree.pt2.at(iBestPair)
eta_2[0] = iTree.eta2.at(iBestPair)
phi_2[0] = iTree.phi2.at(iBestPair)
m_2[0] = iTree.m2.at(iBestPair)
q_2[0] = int(iTree.charge2.at(iBestPair))
iso_2[0] = iTree.tau2MVAIso
mva_2[0] = 0
byCombinedIsolationDeltaBetaCorrRaw3Hits_2[0] = iTree.iso2.at(iBestPair)
d0_2[0] = iTree.d0_2
dZ_2[0] = iTree.l2dz
# mt_2[0] = iTree.mt2
againstElectronMVA3raw_1[0] = iTree.againstElectronMVA3raw_1
againstElectronMVA3raw_2[0] = iTree.againstElectronMVA3raw_2
againstMuonLoose2_1[0] = iTree.againstMuonLoose1.at(iBestPair)
againstMuonLoose2_2[0] = iTree.againstMuonLoose2.at(iBestPair)
againstMuonMedium2_1[0] = iTree.againstMuonMedium2_1
againstMuonMedium2_2[0] = iTree.againstMuonMedium2_2
againstMuonTight2_1[0] = iTree.againstMuonTight2_1
againstMuonTight2_2[0] = iTree.againstMuonTight2_2
met[0] = iTree.metUnc
mvamet[0] = iTree.met.at(iBestPair)
# mvametphi[0] = iTree.metphi.at(iBestPair)
mvacov00[0] = iTree.mvacov00
mvacov01[0] = iTree.mvacov01
mvacov10[0] = iTree.mvacov10
mvacov11[0] = iTree.mvacov11
pzetavis[0] = iTree.pZV
pzetamiss[0] = iTree.pZetaMiss
# pt_tt[0] = iTree.fullPt
njets[0] = int(iTree.njets)
njetspt20[0] = int(iTree.njetspt20)
nbtag[0] = int(iTree.NBTags)
bcsv_1[0] = iTree.CSVJ1
bpt_1[0] = iTree.CSVJ1Pt
beta_1[0] = iTree.CSVJ1Eta
bphi_1[0] = iTree.CSVJ1Phi
bcsv_2[0] = iTree.CSVJ2
bpt_2[0] = iTree.CSVJ2Pt
beta_2[0] = iTree.CSVJ2Eta
bphi_2[0] = iTree.CSVJ2Phi
jpt_1[0] = iTree.J1Pt
jeta_1[0] = iTree.J1Eta
jphi_1[0] = iTree.J1Phi
jptraw_1[0] = iTree.J1PtUncorr
jptunc_1[0] = iTree.J1JECUnc
jmva_1[0] = iTree.jmva_1
jctm_1[0] = iTree.J1Ntot
jpass_1[0] = bool(iTree.jpass_1)
jpt_2[0] = iTree.J2Pt
jeta_2[0] = iTree.J2Eta
jphi_2[0] = iTree.J2Phi
jptraw_2[0] = iTree.J2PtUncorr
jptunc_2[0] = iTree.J2JECUnc
jmva_2[0] = iTree.jmva_2
jctm_2[0] = iTree.J2Ntot
jpass_2[0] = bool(iTree.jpass_2)
# embeddedWeight[0] = iTree.embeddedWeight
# weight[0] = effweight[0]*iTree.decayModeWeight*iTree.embeddedWeight
weight[0] = effweight[0]*iTree.decayModeWeight*iTree.PUWeight
puweight[0] = iTree.PUWeight
m_bb[0] = iTree.mJJ
# m_ttbb[0] = iTree.HMass
# decayModeWeight_1[0] = iTree.decayModeWeight1
# decayModeWeight_2[0] = iTree.decayModeWeight2
# DYWeight[0] = iTree.xs/3504000.0
oTree.Fill()
if track:
print 'saved'
counter += 1
tool.printProcessStatus(iEntry, nEntries, 'Saving to file ')
print ''
print '%i events saved' %counter
oFile.cd()
oTree.Write()
oFile.Close()
print 'Saved file: %s.root' %oFileName
def yieldCalculator(dy_mc, tt_full_mc, dy_embed, tt_embed, massWindow, pairOption = 'iso', nBtag = '', doDraw = False):
yieldForMediumCat = {}
eventCounterForMediumCat = {}
yieldForLooseCat = {}
eventCounterForLooseCat = {}
inclusiveYields = {}
eventCounterForInclusive = {}
bins = [19, 225, 700]
dy_embed_1M = r.TH1F('dy_embed_1M', '', bins[0], bins[1], bins[2])
dy_embed_2M = r.TH1F('dy_embed_2M', '', bins[0], bins[1], bins[2])
tt_embed_1M = r.TH1F('tt_embed_1M', '', bins[0], bins[1], bins[2])
tt_embed_2M = r.TH1F('tt_embed_2M', '', bins[0], bins[1], bins[2])
fileList = [('DY_inclusive', dy_mc), ('tt_inclusive', tt_full_mc), ('DY_embed', dy_embed), ('tt_embed', tt_embed)]
for indexFile in range(len(fileList)):
name = fileList[indexFile][0]
iFile = r.TFile(fileList[indexFile][1])
iTree = iFile.Get('eventTree')
yieldForMediumCat[name+'_1M'] = 0.0
yieldForMediumCat[name+'_2M'] = 0.0
yieldForLooseCat[name+'_1L'] = 0.0
yieldForLooseCat[name+'_2L'] = 0.0
eventCounterForInclusive[name] = 0
eventCounterForMediumCat[name+'_1M'] = 0
eventCounterForMediumCat[name+'_2M'] = 0
eventCounterForLooseCat[name+'_1L'] = 0
eventCounterForLooseCat[name+'_2L'] = 0
total = iTree.GetEntries()
inclusiveYields[name] = 0.0
counter = 0
counter_0 = 0
isEmbed = False
isData = False
if 'emb' in name:
isEmbed = True
if name == 'DY_embed':
isData = True
for i in range(0, total):
tool.printProcessStatus(iCurrent=i+1, total=total, processName = 'Looping sample [%s]' %name, iPrevious=i)
#Fill Histograms
iTree.GetEntry(i)
#get the right pair of taus based on isoMin or ptMax
if (iTree.nElectrons > 0 or iTree.nMuons > 0):
continue
#get event category
signSelection, isoSelection, bTagSelection = makeWholeTools2.findCategory(tree = iTree,
iso = makeWholeSample_cfg.iso,
option = pairOption,
isData = isData,
relaxedRegionOption = makeWholeSample_cfg.Relax,
isEmbed = isEmbed,
usePassJetTrigger = makeWholeSample_cfg.usePassJetTrigger,
nBtag = nBtag)
if signSelection == None or isoSelection == None or bTagSelection == None:
continue
looseTag, mediumTag = getRightBTagCatName(bTagSelection)
if iTree.HLT_Any == 0:
continue
if iTree.ZTT == 0:
continue
if 'tt' not in name:
tmpEventYield = iTree.triggerEff*iTree.decayModeWeight
else:
tmpEventYield = iTree.triggerEff
if massWindow and not makeWholeTools2.passCut(iTree, pairOption):
continue
#calculate inclusiveYield
if (signSelection == "OS") and (isoSelection == "Tight"):
eventCounterForInclusive[name] += 1
if 'data' in iTree.sampleName:
inclusiveYields[name] += tmpEventYield*iTree.embeddedWeight
elif isEmbed:
inclusiveYields[name] += iTree.triggerEff*iTree.xs*0.983*(lumi/tt_semi_InitEvents)*iTree.embeddedWeight*iTree.PUWeight
else:
if not makeWholeTools2.passJetTrigger(iTree):
continue
inclusiveYields[name] += tmpEventYield*iTree.xs*lumi*iTree.PUWeight/(iTree.initEvents+0.0)
else:
continue
fillValue = iTree.fMassKinFit
#calculate category yield
if mediumTag != '0M':
if isEmbed:
if 'data' in iTree.sampleName:
yieldForMediumCat["%s_%s" %(name, mediumTag)] += tmpEventYield*iTree.embeddedWeight
if mediumTag == '1M':
dy_embed_1M.Fill(fillValue, tmpEventYield*iTree.embeddedWeight)
else:
dy_embed_2M.Fill(fillValue, tmpEventYield*iTree.embeddedWeight)
else:
yieldForMediumCat["%s_%s" %(name, mediumTag)] += tmpEventYield*iTree.xs*0.983*(lumi/tt_semi_InitEvents)*iTree.embeddedWeight*iTree.PUWeight
if mediumTag == '1M':
tt_embed_1M.Fill(fillValue, tmpEventYield*iTree.xs*0.983*(lumi/tt_semi_InitEvents)*iTree.embeddedWeight*iTree.PUWeight)
else:
tt_embed_2M.Fill(fillValue, tmpEventYield*iTree.xs*0.983*(lumi/tt_semi_InitEvents)*iTree.embeddedWeight*iTree.PUWeight)
else:
yieldForMediumCat["%s_%s" %(name, mediumTag)] += tmpEventYield*iTree.xs*lumi*iTree.PUWeight/iTree.initEvents
eventCounterForMediumCat["%s_%s" %(name, mediumTag)] += 1
#calculate loose cat yield for embed samples
if isEmbed and (looseTag != '0L'):
if 'data' in iTree.sampleName:
yieldForLooseCat["%s_%s" %(name, looseTag)] += tmpEventYield*iTree.embeddedWeight
else:
yieldForLooseCat["%s_%s" %(name, looseTag)] += tmpEventYield*iTree.embeddedWeight*iTree.xs*0.983*lumi/tt_semi_InitEvents
eventCounterForLooseCat["%s_%s" %(name, looseTag)] += 1
print ''
if isEmbed:
print name
print 'inclusive yield for %s: %.2f +/- %.2f' %(name, inclusiveYields[name], calcSysUncSingle(inclusiveYields[name], eventCounterForInclusive[name]))
print '1-Medium %s yield: %.2f +/- %.2f \t events: %i' %(name, yieldForMediumCat[name+'_1M'], calcSysUncSingle(yieldForMediumCat[name+'_1M'], eventCounterForMediumCat[name+'_1M']), eventCounterForMediumCat[name+'_1M'])
print '1-Loose %s yield: %.2f +/- %.2f \t events: %i' %(name, yieldForLooseCat[name+'_1L'], calcSysUncSingle(yieldForLooseCat[name+'_1L'], eventCounterForLooseCat[name+'_1L']), eventCounterForLooseCat[name+'_1L'])
print '2-Medium %s yield: %.2f +/- %.2f \t events: %i' %(name, yieldForMediumCat[name+'_2M'], calcSysUncSingle(yieldForMediumCat[name+'_2M'], eventCounterForMediumCat[name+'_2M']), eventCounterForMediumCat[name+'_2M'])
print '2-Loose %s yield: %.2f +/- %.2f \t events: %i' %(name, yieldForLooseCat[name+'_2L'], calcSysUncSingle(yieldForLooseCat[name+'_2L'], eventCounterForLooseCat[name+'_2L']), eventCounterForLooseCat[name+'_2L'])
else:
print 'inclusive yield for %s: %.2f' %(name, inclusiveYields[name])
delta_dy_inclusive = calcSysUncSingle(inclusiveYields['DY_embed'], eventCounterForInclusive['DY_embed'])
delta_tt_inclusive = calcSysUncSingle(inclusiveYields['tt_embed'], eventCounterForInclusive['tt_embed'])
delta_dy_1M = calcSysUncSingle(yieldForMediumCat['DY_embed_1M'], eventCounterForMediumCat['DY_embed_1M'])
delta_tt_1M = calcSysUncSingle(yieldForMediumCat['tt_embed_1M'], eventCounterForMediumCat['tt_embed_1M'])
delta_dy_2M = calcSysUncSingle(yieldForMediumCat['DY_embed_2M'], eventCounterForMediumCat['DY_embed_2M'])
delta_tt_2M = calcSysUncSingle(yieldForMediumCat['tt_embed_2M'], eventCounterForMediumCat['tt_embed_2M'])
sysUnc_1M = calcSysUnc(sf = (yieldForMediumCat['DY_embed_1M']-yieldForMediumCat['tt_embed_1M'])/(inclusiveYields['DY_embed'] - inclusiveYields['tt_embed']),
numA = yieldForMediumCat['DY_embed_1M'],
numB = yieldForMediumCat['tt_embed_1M'],
denomA = inclusiveYields['DY_embed'],
denomB = inclusiveYields['tt_embed'],
delta_numA = delta_dy_1M,
delta_numB = delta_tt_1M,
delta_denomA = delta_dy_inclusive,
delta_denomB = delta_tt_inclusive)
sysUnc_2M = calcSysUnc(sf = (yieldForMediumCat['DY_embed_2M']-yieldForMediumCat['tt_embed_2M'])/(inclusiveYields['DY_embed'] - inclusiveYields['tt_embed']),
numA = yieldForMediumCat['DY_embed_2M'],
numB = yieldForMediumCat['tt_embed_2M'],
denomA = inclusiveYields['DY_embed'],
denomB = inclusiveYields['tt_embed'],
delta_numA = delta_dy_2M,
delta_numB = delta_tt_2M,
delta_denomA = delta_dy_inclusive,
delta_denomB = delta_tt_inclusive)
sysUnc_xs_1M = calcSysUnc(sf = (yieldForMediumCat['DY_embed_1M']-yieldForMediumCat['tt_embed_1M'])/(inclusiveYields['DY_embed'] - inclusiveYields['tt_embed']),
numA = yieldForMediumCat['DY_embed_1M'],
numB = yieldForMediumCat['tt_embed_1M'],
denomA = inclusiveYields['DY_embed'],
denomB = inclusiveYields['tt_embed'],
delta_numA = 0,
delta_numB = yieldForMediumCat['tt_embed_1M']*0.1,
delta_denomA = 0,
delta_denomB = inclusiveYields['tt_embed']*0.1)
sysUnc_xs_2M = calcSysUnc(sf = (yieldForMediumCat['DY_embed_2M']-yieldForMediumCat['tt_embed_2M'])/(inclusiveYields['DY_embed'] - inclusiveYields['tt_embed']),
numA = yieldForMediumCat['DY_embed_2M'],
numB = yieldForMediumCat['tt_embed_2M'],
denomA = inclusiveYields['DY_embed'],
denomB = inclusiveYields['tt_embed'],
delta_numA = 0,
delta_numB = yieldForMediumCat['tt_embed_2M']*0.1,
delta_denomA = 0,
delta_denomB = inclusiveYields['tt_embed']*0.1)
preScaleFactor = inclusiveYields['DY_inclusive']/(inclusiveYields['DY_embed'] - inclusiveYields['tt_embed'])
scaleFactor_1M = preScaleFactor*(yieldForMediumCat['DY_embed_1M']-yieldForMediumCat['tt_embed_1M'])
scaleFactor_2M = preScaleFactor*(yieldForMediumCat['DY_embed_2M']-yieldForMediumCat['tt_embed_2M'])
preScaleFactor2 = (inclusiveYields['DY_inclusive']+inclusiveYields['tt_inclusive'])/(inclusiveYields['DY_embed'])
scaleFactor_1M2 = preScaleFactor2*(yieldForMediumCat['DY_embed_1M'])
scaleFactor_2M2 = preScaleFactor2*(yieldForMediumCat['DY_embed_2M'])
print ''
print 'predicted DY in 1M: %.2fx(%.2f +/- %.2f - %.2f +/- %.2f)/(%.2f +/- %.2f - %.2f +/- %.2f) = %.2f +/- %.2f%% (statistical)' %(inclusiveYields['DY_inclusive'],
yieldForMediumCat['DY_embed_1M'],
calcSysUncSingle(yieldForMediumCat['DY_embed_1M'], eventCounterForMediumCat['DY_embed_1M']),
yieldForMediumCat['tt_embed_1M'],
calcSysUncSingle(yieldForMediumCat['tt_embed_1M'], eventCounterForMediumCat['tt_embed_1M']),
inclusiveYields['DY_embed'],
calcSysUncSingle(inclusiveYields['DY_embed'], eventCounterForInclusive['DY_embed']),
inclusiveYields['tt_embed'],
calcSysUncSingle(inclusiveYields['tt_embed'], eventCounterForInclusive['tt_embed']),
scaleFactor_1M,
sysUnc_1M*inclusiveYields['DY_inclusive']/scaleFactor_1M*100
)
print 'predicted DY in 2M: %.2fx(%.2f +/- %.2f - %.2f +/- %.2f)/(%.2f +/- %.2f - %.2f +/- %.2f) = %.2f +/- %.2f%% (statistical)' %(inclusiveYields['DY_inclusive'],
yieldForMediumCat['DY_embed_2M'],
calcSysUncSingle(yieldForMediumCat['DY_embed_2M'], eventCounterForMediumCat['DY_embed_2M']),
yieldForMediumCat['tt_embed_2M'],
calcSysUncSingle(yieldForMediumCat['tt_embed_2M'], eventCounterForMediumCat['tt_embed_2M']),
inclusiveYields['DY_embed'],
calcSysUncSingle(inclusiveYields['DY_embed'], eventCounterForInclusive['DY_embed']),
inclusiveYields['tt_embed'],
calcSysUncSingle(inclusiveYields['tt_embed'], eventCounterForInclusive['tt_embed']),
scaleFactor_2M,
sysUnc_2M*inclusiveYields['DY_inclusive']/scaleFactor_2M*100
)
print ''
print 'predicted DY in 1M: %.2fx(%.2f - %.2f +/- %.2f)/(%.2f - %.2f +/- %.2f) = %.2f +/- %.2f%% (tt_xs)' %(inclusiveYields['DY_inclusive'],
yieldForMediumCat['DY_embed_1M'],
yieldForMediumCat['tt_embed_1M'],
yieldForMediumCat['tt_embed_1M']*0.1,
inclusiveYields['DY_embed'],
inclusiveYields['tt_embed'],
inclusiveYields['tt_embed']*0.1,
scaleFactor_1M,
sysUnc_xs_1M*inclusiveYields['DY_inclusive']/scaleFactor_1M*100
)
print 'predicted DY in 2M: %.2fx(%.2f - %.2f +/- %.2f)/(%.2f - %.2f +/- %.2f) = %.2f +/- %.2f%% (tt_xs)' %(inclusiveYields['DY_inclusive'],
yieldForMediumCat['DY_embed_2M'],
yieldForMediumCat['tt_embed_2M'],
yieldForMediumCat['tt_embed_2M']*0.1,
inclusiveYields['DY_embed'],
inclusiveYields['tt_embed'],
inclusiveYields['tt_embed']*0.1,
scaleFactor_2M,
sysUnc_xs_2M*inclusiveYields['DY_inclusive']/scaleFactor_2M*100
)
print ''
print 'DY MC in 1M: %.2f' %yieldForMediumCat['DY_inclusive_1M']
print 'DY MC in 2M: %.2f' %yieldForMediumCat['DY_inclusive_2M']
# print 'predicted DY+tt in 1M: %.2f' %scaleFactor_1M2
# print 'predicted DY+tt in 2M: %.2f' %scaleFactor_2M2
if doDraw:
position = (0.6, 0.9 - 0.06*2, 0.87, 0.9)
l1 = tool.setMyLegend(position, [(dy_embed_1M, 'dy_embed_1M'), (tt_embed_1M, 'tt_embed_1M')])
l2 = tool.setMyLegend(position, [(dy_embed_2M, 'dy_embed_2M'), (tt_embed_2M, 'tt_embed_2M')])
psfile = 'DY_embed_tauUp.pdf'
c = r.TCanvas("c","Test", 800, 600)
dy_embed_1M.Draw()
dy_embed_1M.SetTitle(';fMassKinFit;')
tt_embed_1M.SetLineStyle(2)
tt_embed_1M.SetLineColor(r.kRed)
tt_embed_1M.Draw('same')
l1.Draw('same')
c.Print('%s(' %psfile)
dy_embed_2M.Draw()
dy_embed_2M.SetTitle(';fMassKinFit;')
tt_embed_2M.SetLineStyle(2)
tt_embed_2M.SetLineColor(r.kRed)
tt_embed_2M.Draw('same')
l2.Draw('same')
c.Print('%s)' %psfile)
return scaleFactor_1M, scaleFactor_2M, scaleFactor_1M2, scaleFactor_2M2, preScaleFactor
def l2MYieldCalculator(sample, massWindow, pairOption = 'iso', nBtag = '', ZLL = False):
yieldForMediumCat = {}
yieldForLooseCat = {}
eventCounterForMediumCat = {}
eventCounterForLooseCat = {}
iFile = r.TFile(sample)
iTree = iFile.Get('eventTree')
yieldForMediumCat['1M'] = 0.0
yieldForMediumCat['2M'] = 0.0
yieldForLooseCat['1L'] = 0.0
yieldForLooseCat['2L'] = 0.0
eventCounterForMediumCat['1M'] = 0.0
eventCounterForMediumCat['2M'] = 0.0
eventCounterForLooseCat['1L'] = 0.0
eventCounterForLooseCat['2L'] = 0.0
total = iTree.GetEntries()
for i in range(0, total):
tool.printProcessStatus(iCurrent=i+1, total=total, processName = 'Looping sample [%s]' %sample, iPrevious=i)
iTree.GetEntry(i)
#get the right pair of taus based on isoMin or ptMax
if (iTree.nElectrons > 0 or iTree.nMuons > 0):
continue
if not makeWholeTools2.passJetTrigger(iTree):
continue
if ZLL and iTree.ZLL == 0:
continue
#get event category
signSelection, isoSelection, bTagSelection = makeWholeTools2.findCategory(tree = iTree,
iso = makeWholeSample_cfg.iso,
option = pairOption,
isData = False,
relaxedRegionOption = makeWholeSample_cfg.Relax,
isEmbed = False,
usePassJetTrigger = makeWholeSample_cfg.usePassJetTrigger,
nBtag = nBtag)
if signSelection == None or isoSelection == None:
continue
looseTag, mediumTag = getRightBTagCatName(bTagSelection)
if massWindow and not makeWholeTools2.passCut(iTree, pairOption):
continue
#calculate category yield
if (signSelection == "OS") and (isoSelection == "Tight") and (mediumTag != '0M'):
yieldForMediumCat[mediumTag] += iTree.triggerEff*iTree.xs*lumi*iTree.PUWeight/iTree.initEvents
eventCounterForMediumCat[mediumTag] += 1
#calculate loose cat yield for embed samples
if (signSelection == "OS") and (isoSelection == "Tight") and (looseTag != '0L'):
yieldForLooseCat[looseTag] += iTree.triggerEff*iTree.xs*lumi*iTree.PUWeight/iTree.initEvents
eventCounterForLooseCat[looseTag] += 1
print ''
scaleFactor_1M = yieldForMediumCat['1M']/yieldForLooseCat['1L']
scaleFactor_2M = yieldForMediumCat['2M']/yieldForLooseCat['2L']
print '[%s] (1L): %.2f %.0f'%(sample, yieldForLooseCat['1L'], eventCounterForLooseCat['1L'])
print '[%s] (2L): %.2f %.0f'%(sample, yieldForLooseCat['2L'], eventCounterForLooseCat['2L'])
print '[%s] (1M): %.2f %.0f'%(sample, yieldForMediumCat['1M'], eventCounterForMediumCat['1M'])
print '[%s] (2M): %.2f %.0f'%(sample, yieldForMediumCat['2M'], eventCounterForMediumCat['2M'])
unc_1M = calcSysUncSingle(yieldForMediumCat['1M'], eventCounterForMediumCat['1M'])
unc_2M = calcSysUncSingle(yieldForMediumCat['2M'], eventCounterForMediumCat['2M'])
print '1M: %.2f +/- %.1f%%' %(yieldForMediumCat['1M'], unc_1M*100/yieldForMediumCat['1M'])
print '2M: %.2f +/- %.1f%%' %(yieldForMediumCat['2M'], unc_2M*100/yieldForMediumCat['2M'])
return yieldForMediumCat['1M'], yieldForMediumCat['2M']
def run():
fileList = []
for i in range(len(makeWholeSample_cfg.sampleConfigs)):
#configs name, location, selection, useMediumForYield
fileList.append((makeWholeSample_cfg.sampleConfigs[i][0],
makeWholeSample_cfg.sampleConfigs[i][1],
makeWholeSample_cfg.sampleConfigs[i][2],
makeWholeSample_cfg.sampleConfigs[i][3]))
if makeWholeSample_cfg.sampleConfigs[i][0] == 'DY_inclusive':
dy_mc = makeWholeSample_cfg.sampleConfigs[i][1]
if makeWholeSample_cfg.sampleConfigs[i][0] == 't#bar{t}':
tt_full_mc = makeWholeSample_cfg.sampleConfigs[i][1]
if makeWholeSample_cfg.sampleConfigs[i][0] == 'DY_embed':
dy_embed = makeWholeSample_cfg.sampleConfigs[i][1]
if makeWholeSample_cfg.sampleConfigs[i][0] == 'tt_embed':
tt_embed = makeWholeSample_cfg.sampleConfigs[i][1]
oFileName = makeWholeSample_cfg.oFileName
oFile = r.TFile(oFileName, 'RECREATE')
oTree = r.TTree('eventTree', '')
iso = makeWholeSample_cfg.iso
nSamples = len(fileList)
mJJ = array('f', [0.])
svMass = array('f', [0.])
fMass = array('f', [0.])
fMassKinFit = array('f', [0.])
chi2KinFit = array('f', [0.])
chi2KinFit2 = array('f', [0.])
PUWeight = array('f', [0.])
iso1 = array('f', [0.])
iso2 = array('f', [0.])
pt1 = array('f', [0.])
pt2 = array('f', [0.])
CSVJ1Pt = array('f', [0.])
CSVJ2Pt = array('f', [0.])
CSVJ2 = array('f', [0.])
NBTags = array('i', [0])
triggerEff = array('f', [0.])
sampleName = bytearray(20)
genMatchName = bytearray(3)
xs = array('f', [0.])
embeddedWeight = array('f', [0.])
decayModeWeight = array('f', [0.])
initEvents = array('f', [0.])
Category = bytearray(5)
xsValues = {}
initEventsValues = {}
eventsSaved = {}
yieldForMediumCat = {}
inclusiveYields = {}
inclusiveYields = {}
catYields = {}
svMassRange = [20, 0, 400]
L2T_value = 0
oTree.Branch("mJJ", mJJ, "mJJ/F")
oTree.Branch("fMass", fMass, "fMass/F")
oTree.Branch("fMassKinFit", fMassKinFit, "fMassKinFit/F")
oTree.Branch("chi2KinFit", chi2KinFit, "chi2KinFit/F")
oTree.Branch("chi2KinFit2", chi2KinFit2, "chi2KinFit2/F")
oTree.Branch("xs", xs, "xs/F")
oTree.Branch("initEvents", initEvents, "initEvents/F")
oTree.Branch("NBTags", NBTags, "NBTags/I")
oTree.Branch("Category", Category, "Category[21]/C")
oTree.Branch("svMass", svMass, "svMass/F")
oTree.Branch("CSVJ2", CSVJ2, "CSVJ2/F")
oTree.Branch("iso1", iso1, "iso1/F")
oTree.Branch("iso2", iso2, "iso2/F")
oTree.Branch("pt1", pt1, "pt1/F")
oTree.Branch("pt2", pt2, "pt2/F")
oTree.Branch("CSVJ1Pt", CSVJ1Pt, "CSVJ1Pt/F")
oTree.Branch("CSVJ2Pt", CSVJ2Pt, "CSVJ2Pt/F")
oTree.Branch("triggerEff", triggerEff, "triggerEff/F")
oTree.Branch("PUWeight", PUWeight, "PUWeight/F")
oTree.Branch("embeddedWeight", embeddedWeight, "embeddedWeight/F")
oTree.Branch("decayModeWeight", decayModeWeight, "decayModeWeight/F")
oTree.Branch("sampleName", sampleName, "sampleName[21]/C")
oTree.Branch("genMatchName", genMatchName, "genMatchName[21]/C")
for indexFile in range(nSamples):
eventsSavedCounter_1M = 0.0
eventsSavedCounter_2M = 0.0
name = fileList[indexFile][0]
option = fileList[indexFile][2]
iFile = r.TFile(fileList[indexFile][1])
iTree = iFile.Get('eventTree')
useMediumCat4Yield = fileList[indexFile][3]
if useMediumCat4Yield:
yieldForMediumCat[name+'_1M'] = 0.0
yieldForMediumCat[name+'_2M'] = 0.0
total = iTree.GetEntries()
isData = False
if ('data' in name) or ('DY_embed' in name):
isData = True
if 'emb' in name:
isEmbed = True
inclusiveYields[name] = 0.0
else:
isEmbed = False
if 'inclusive' in name:
isInclusive = True
inclusiveYields[name] = 0.0
else:
isInclusive = False
cat = ''
region = 'bTag'
if '1M' in option:
region = '1M'
elif '2M' in option:
region = '2M'
elif '1L' in option:
region = '1L'
cat = '1M'
elif '2L' in option:
region = '2L'
cat = '2M'
for i in range(0, total):
tool.printProcessStatus(iCurrent=i+1, total=total, processName = 'Looping sample [%s]' %name, iPrevious=i)
#Fill Histograms
iTree.GetEntry(i)
#get the right pair of taus based on isoMin or ptMax
rightPair = makeWholeTools2.findRightPair(iTree, makeWholeSample_cfg.pairOption)
if makeWholeSample_cfg.thirdLeptonVeto and (iTree.nElectrons > 0 or iTree.nMuons > 0):
continue
if iTree.HLT_Any == 0:
continue
#get event category
signSelection, isoSelection, bTagSelection = makeWholeTools2.findCategory(tree = iTree,
iso = makeWholeSample_cfg.iso,
option = makeWholeSample_cfg.pairOption,
isData = isData,
relaxedRegionOption = makeWholeSample_cfg.Relax,
isEmbed = isEmbed,
usePassJetTrigger = makeWholeSample_cfg.usePassJetTrigger,
nBtag = makeWholeSample_cfg.bTagShift)
if signSelection == None or isoSelection == None or bTagSelection == None:
continue
looseTag, mediumTag = getRightBTagCatName(bTagSelection)
if isEmbed and iTree.ZTT == 0:
continue
if name == 'ZLL' and iTree.ZLL == 0:
continue
if name == 'ZTT' and iTree.ZTT == 0:
continue
#calculate category yield
if useMediumCat4Yield:
if (not makeWholeSample_cfg.massWindow) or (makeWholeSample_cfg.massWindow and makeWholeTools2.passCut(iTree, makeWholeSample_cfg.pairOption)):
if (signSelection == "OS") and (isoSelection == "Tight") and (mediumTag != '0M'):
if isEmbed:
if 'data' in iTree.sampleName:
yieldForMediumCat["%s_%s" %(name, mediumTag)] += iTree.triggerEff
else:
yieldForMediumCat["%s_%s" %(name, mediumTag)] += iTree.triggerEff*iTree.xs*0.983*lumi/tt_semi_InitEvents
elif name == 'ZLL':
yieldForMediumCat["%s_%s" %(name, mediumTag)] += iTree.triggerEff*iTree.xs*lumi*iTree.PUWeight*iTree.decayModeWeight/iTree.initEvents
else:
yieldForMediumCat["%s_%s" %(name, mediumTag)] += iTree.triggerEff*iTree.xs*lumi*iTree.PUWeight/iTree.initEvents
passSelection, bRegion = passCut(option, signSelection, isoSelection, looseTag, mediumTag)
if option[:len(option)-1] != signSelection+isoSelection:
continue
mJJ[0] = iTree.mJJ
fMass[0] = iTree.fMass
fMassKinFit[0] = iTree.fMassKinFit
chi2KinFit[0] = iTree.chi2KinFit
chi2KinFit2[0] = iTree.chi2KinFit2
svMass[0] = iTree.svMass.at(rightPair)
iso1[0] = iTree.iso1.at(rightPair)
iso2[0] = iTree.iso2.at(rightPair)
CSVJ2[0] = iTree.CSVJ2
NBTags[0] = int(iTree.NBTags)
triggerEff[0] = iTree.triggerEff
pt1[0] = iTree.pt1.at(rightPair)
pt2[0] = iTree.pt2.at(rightPair)
CSVJ1Pt[0] = iTree.CSVJ1Pt
CSVJ2Pt[0] = iTree.CSVJ2Pt
decayModeWeight[0] = 1.0
embeddedWeight[0] = 1.0
if '_semi' not in iTree.sampleName:
tmpSampleName = iTree.sampleName[0:iTree.sampleName.find('_')]
else:
tmpSampleName = iTree.sampleName[0:iTree.sampleName.find('_semi')+5]
if 'data' in tmpSampleName and (not isEmbed):
sampleName[:21] = name
initEvents[0] = 1.0
xs[0] = 1.0
elif ('data' in tmpSampleName) and isEmbed:
sampleName[:21] = 'DY_embed'
initEvents[0] = 1.0
xs[0] = 1.0
embeddedWeight[0] = iTree.embeddedWeight
decayModeWeight[0] = iTree.decayModeWeight
elif not isEmbed:
if name == 'signals':
decayModeWeight[0] = iTree.decayModeWeight
initEvents[0] = iTree.initEvents
xs[0] = iTree.xs
sampleName[:21] = tmpSampleName
if name == 'MCOSRelax':
sampleName[:21] = 'MCOSRelax'
if 'HToTauTau' in name:
sampleName[:21] = name
elif name == 'ZLL':
sampleName[:21] = 'ZLL'
decayModeWeight[0] = iTree.decayModeWeight
elif name == 'ZTT':
sampleName[:21] = 'ZTT'
decayModeWeight[0] = iTree.decayModeWeight
else:
initEvents[0] = tt_semi_InitEvents
xs[0] = iTree.xs*0.983
sampleName[:21] = 'tt_embed'
embeddedWeight[0] = iTree.embeddedWeight
decayModeWeight[0] = iTree.decayModeWeight
if str(sampleName) not in initEventsValues.keys():
if 'data' not in str(sampleName):
initEventsValues[str(sampleName)] = iTree.initEvents
xsValues[str(sampleName)] = iTree.xs
eventsSaved[str(sampleName)] = 0.0
# genMatchName[:3] = findMatch(iTree, isData, rightPair)
if isData:
PUWeight[0] = 1.0
else:
PUWeight[0] = iTree.PUWeight
if mediumTag == '0M':
Category[:21] = '0M'
oTree.Fill()
if passSelection:
Category[:21] = bRegion
oTree.Fill()
else:
continue
if makeWholeSample_cfg.massWindow and (not makeWholeTools2.passCut(iTree, makeWholeSample_cfg.pairOption)):
continue
if isData:
eventsSaved[str(sampleName)] += 1
if bRegion == '1M':
eventsSavedCounter_1M += 1
elif bRegion == '2M':
eventsSavedCounter_2M += 1
elif not isEmbed:
eventsSaved[str(sampleName)] += triggerEff[0]
if bRegion == '1M':
eventsSavedCounter_1M += triggerEff[0]*xsValues[str(sampleName)]/initEventsValues[str(sampleName)]*PUWeight[0]*lumi
elif bRegion == '2M':
eventsSavedCounter_2M += triggerEff[0]*xsValues[str(sampleName)]/initEventsValues[str(sampleName)]*PUWeight[0]*lumi
print ' --- Events Saved: (1M) %.2f (2M) %.2f' %(eventsSavedCounter_1M, eventsSavedCounter_2M)
if isEmbed:
print name
print 'inclusive yield for %s: %.2f' %(name, inclusiveYields[name])
print '1-Medium category yield for %s: %.2f' %(name, yieldForMediumCat[name+'_1M'])
print '2-Medium category yield for %s: %.2f' %(name, yieldForMediumCat[name+'_2M'])
elif isInclusive:
print 'inclusive yield for %s: %.2f' %(name, inclusiveYields[name])
nSamples = len(initEventsValues.keys())
initEvents = r.TH1F('initEvents', '', nSamples, 0, nSamples)
xsHist = r.TH1F('xs', '', nSamples, 0, nSamples)
for iKey in initEventsValues.keys():
if 'data' not in iKey:
initEvents.Fill(iKey, initEventsValues[iKey])
xsHist.Fill(iKey, xsValues[iKey])
weights = makeWholeTools2.calculateSF(fileList = makeWholeSample_cfg.sampleConfigsTools,
sigRegionOption = 'Tight',
relaxedRegionOption = makeWholeSample_cfg.Relax,
verbose = True,
isoTight = 1.0,
pairOption = makeWholeSample_cfg.pairOption,
massWindow = makeWholeSample_cfg.massWindow,
usePassJetTrigger = makeWholeSample_cfg.usePassJetTrigger,
nBtag = '')
scaleFactor_1M, scaleFactor_2M, scaleFactor_1M2, scaleFactor_2M2, preScaleFactor = embedDYYieldCalculator.yieldCalculator(dy_mc = dy_mc,
tt_full_mc = tt_full_mc,
dy_embed = dy_embed,
tt_embed = tt_embed,
massWindow = makeWholeSample_cfg.massWindow,
pairOption = makeWholeSample_cfg.pairOption)
print weights
#define histograms
L_to_T_SF_0M = r.TH1F('L_to_T_SF_0M', '', 1, 0, 1)
MC2Embed2Cat_0M = r.TH1F('MC2Embed2Cat_0M', '', 1, 0, 1)
L_to_T_1M = r.TH1F('L_to_T_1M', '', 1, 0, 1)
L_to_T_SF_1M = r.TH1F('L_to_T_SF_1M', '', 1, 0, 1)
MC2Embed2Cat_1M = r.TH1F('MC2Embed2Cat_1M', '', 1, 0, 1)
EmbedWithTTLep_1M = r.TH1F('EmbedWithTTLep_1M', '', 1, 0, 1)
DYwithTTScale_1M = r.TH1F('DYwithTTScale_1M', '', 1, 0, 1)
L_to_T_2M = r.TH1F('L_to_T_2M', '', 1, 0, 1)
L_to_T_SF_2M = r.TH1F('L_to_T_SF_2M', '', 1, 0, 1)
MC2Embed2Cat_2M = r.TH1F('MC2Embed2Cat_2M', '', 1, 0, 1)
EmbedWithTTLep_2M = r.TH1F('EmbedWithTTLep_2M', '', 1, 0, 1)
DYwithTTScale_2M = r.TH1F('DYwithTTScale_2M', '', 1, 0, 1)
yieldForMediumCatHists = {}
#save histograms
L_to_T_1M.Fill(0.5, weights[0])
L_to_T_2M.Fill(0.5, weights[1])
L_to_T_SF_1M.Fill(0.5, weights[2])
L_to_T_SF_2M.Fill(0.5, weights[3])
L_to_T_SF_0M.Fill(0.5, weights[4])
# preScaleFactor = inclusiveYields['DY_inclusive']/(inclusiveYields['DY_embed'] - inclusiveYields['tt_embed'])
# scaleFactor_1M = preScaleFactor*(yieldForMediumCat['DY_embed_1M']-yieldForMediumCat['tt_embed_1M'])
# scaleFactor_2M = preScaleFactor*(yieldForMediumCat['DY_embed_2M']-yieldForMediumCat['tt_embed_2M'])
MC2Embed2Cat_0M.Fill(0.5, preScaleFactor)
MC2Embed2Cat_1M.Fill(0.5, scaleFactor_1M)
MC2Embed2Cat_2M.Fill(0.5, scaleFactor_2M)
DYwithTTScale_1M.Fill(0.5, scaleFactor_1M2)
DYwithTTScale_2M.Fill(0.5, scaleFactor_2M2)
print 'Embed DY prediction (1M): %.2f' %scaleFactor_1M
print 'Embed DY prediction (2M): %.2f' %scaleFactor_2M
oFile.cd()
initEvents.Write()
xsHist.Write()
L_to_T_1M.Write()
L_to_T_SF_1M.Write()
L_to_T_2M.Write()
L_to_T_SF_2M.Write()
L_to_T_SF_0M.Write()
MC2Embed2Cat_0M.Write()
MC2Embed2Cat_1M.Write()
MC2Embed2Cat_2M.Write()
DYwithTTScale_1M.Write()
DYwithTTScale_2M.Write()
for iKey in yieldForMediumCat.keys():
yieldForMediumCatHists[iKey] = r.TH1F(iKey, '', 1, 0, 1)
yieldForMediumCatHists[iKey].Fill(0.5, yieldForMediumCat[iKey])
print '%s prediction: %.2f' %(iKey, yieldForMediumCat[iKey])
yieldForMediumCatHists[iKey].Write()
oTree.Write()
oFile.Close()
print 'Combined event saved at: %s' %oFileName